Data management report (pre-SA YSJ data)

MAXOUT-Study Abroad (YSJ)

Authors
Affiliations

Chris Moreh

Newcastle University

Chisato Danjo

York St John University

Yeji Han

York St John University

Joan Walton

York St John University

Linda Walz

Leeds Trinity University

Abstract

This report details the data management and preparation workflow of the project.

Keywords

DRAFT; data management

Click to see code 
#### ---- Packages ---- ######################################################## 

# install.packages("pacman")

if (!require("pacman")) install.packages("pacman")

pacman::p_load(
  tidyverse,
  summarytools,
  easystats,
  readxl,
  DT,
  flextable,
  here,
  fs
  )

pacman::p_load_gh(
  "strengejacke/strengejacke"
  )

### Package settings

DT:::DT2BSClass(c('compact', 'cell-border'))

Raw data

In order to ensure end-to-end reproducibility in our data management workflow, the code included in this report is used to operate directly on the raw data downloaded from Qualtrics. The data files are downloaded into a folder called data_raw with their default Qualtrics names, which includes the survey name plus the date and time of the download. The data is exported from Qualtrics as SPSS .sav data files with the extra long labels option.

The data_raw folder contains the following files on 2024-01-15:

Click to see code 
### `data_raw` directory status

fs::dir_info("data_raw")[, c(1,3)] |> flextable::qflextable() |> flextable::fontsize(size = 10)

path

size

data_raw/postSA_YSJ_2023_January+4,+2024_07.39.sav

7.29M

data_raw/preSA_YSJ_2023_January+14,+2024_19.08.sav

16.85M

data_raw/Study Abroad Expectations_September 11, 2023_17.06.sav

43.24M

data_raw/Study+Abroad+Expectations+–+External_September+11,+2023_17.09.sav

23.82M

data_raw/survey_coding.xlsx

59.57K

Click to see code 
### Import from raw ------------------------------------------------------------
here()

raw <- list.files("data_raw", pattern = "\\.sav")                               # List files with the `.sav` extension
codeplan <- list.files("data_raw", pattern = "\\.xlsx")                         # List files with the `.xlsx` extension
raw

postSA23_ysj <- file.path("data_raw", raw[1])                                   # 2023 YSJ 3rd-year returnee YSJ student data
preSA23_ysj <- file.path("data_raw", raw[2])                                    # 2023 YSJ 1st-year data
preSA20_ysj <- file.path("data_raw", raw[3])                                    # 2020 YSJ student data
preSA20_ext <- file.path("data_raw", raw[4])                                    # 2020 Non-YSJ student data
codeplan <- file.path("data_raw", codeplan[1])                                  # Excel survey codebook


preSA20_ysj <- read_spss(preSA20_ysj)
preSA20_ysj <- preSA20_ysj |> select(!Q88)                                      # Remove YSJ-specific interview invitation
preSA20_ext <- read_spss(preSA20_ext)                         
sa <- add_rows(preSA20_ysj, preSA20_ext)                                        # Merge YSJ and External data
sa <- sa |> 
  select(!c(Q1_1,                                                               # Remove PIS question
            contains("Topics"))                                                 # Remove questionnaire topic header data columns from the end
         )

We import and merge the 2020 YSJ and External data-sets to obtain a data frame of the combined raw data with 184 cases/rows and 302 variables/columns.

Because the survey questions were broken down by language studied (Japanese/Korean), we have duplicate variables coding the same question (prefixed with “A1_” for Japanese and “A2_” for Korean). To unify the variables, we use the survey codebook saved as an Excel sheet. A further complication is that the Qualtrics questionnaire included piped text for Japanese and Korean language students, and these show with with non-human-readable characters in the variable and value labels, so we replace these characters with the phrase “JP/KO”.

Click to see code 
### Variable names and labels --------------------------------------------------

varnames <- read_xlsx(codeplan, sheet = 2, range = "I1:I303") |> t()            # Transpose (`t()`) the dataframe to get string vector
varlabs <- read_xlsx(codeplan, sheet = 2, range = "J1:J303") |> t()
  
sa <- sjlabelled::set_label(sa, varlabs)                                     
names(sa) <- varnames

# sa_test <- sa   # for testing changes below

## Need to replace shortcodes for "Japanese" and "Korean"

labs <- sjlabelled::get_labels(sa)                                              # get all value labels as list

labs <- lapply(labs, function(x) str_replace_all(x,                             # Change all the values labels in all the variables in list
                               '\\$[^\\}]*\\}', 
                               "JP/KO"))

sa <- sjlabelled::set_labels(sa, labels = labs, force.labels = T)               # apply changed labels to dataset; keep labels as attribute (don't do `as_label(as.numeric)` beforehand)


sa |> frq(contains("_img_"), "A1_expect_socialise")                             # quick check


### Convert labelled factor variables ------------------------------------------

sa <- sa |> 
    mutate(across(where(is.factor), sjlabelled::as_numeric),
           across(everything(), sjlabelled::as_label))


### Unify variables split by language ------------------------------------------

sa_korean <- sa |> 
  filter(language == "Korean") |>
  select(!starts_with("A1")) |> 
  rename_with(stringr::str_replace,
              pattern = "A2_", replacement = "",
              matches("A2_"))


sa_japanese <- sa |> 
  filter(language == "Japanese") |>
  select(!starts_with("A2")) |> 
  rename_with(stringr::str_replace,
              pattern = "A1_", replacement = "",
              matches("A1_"))

sa_missing <- sa |>
  filter(is.na(language))                                                   # 10 observations are missing language variable


sa <- sjmisc::add_rows(sa_japanese, sa_korean)                              # this keeps `label` attribute but not other non-relevant attributes
                                                                            ## `bind_rows` removes the variable labels
                                                                            ## `datawizard::data_merge` may keep all SPSS-specific information, such as `display_width` and `format.spss`

sa |> frq(contains("img_"), "expect_socialise")                             # quick check again

The unified data-frame now contains 174 cases/rows and 185 variables/columns.

Protected data

We can select out variables that contain more sensitive information to store separately from the main analysis dataset.

Some of this information (e.g. e-mail) was collected for the purposes of contacting students who opted in for participation in a follow-up qualitative interview and/or future (post-SA) rounds of data collection. We check and recode those who agreed to a follow-up, creating a new variables coding data collection Cohort

Respondent e-mail addresses and IP Addresses are also helpful for identifying any data reliability issues, such as duplicate responses. (n.b. the IPAddress collected by Qualtrics is “external”, so those connecting to the same network will share an IP). We find two email addresses with duplicate responses, and we will keep the earlier responses, deleting the two later responses from the analysis dataset. The reason for this choice is that later responses could be contaminated by having previously completed the survey already.

Following the checks and the cleansing, we remove the sensitive data from the main analysis dataset.

Click to see code 
### Follow-up study by Cohort and Uni

sa <- sa |> 
  mutate(
    cohort = case_when(
      StartDate < as.POSIXct("2020-09-01") ~ "2019/2020",
      StartDate >= as.POSIXct("2020-09-01") ~ "2020/2021"),                 # calculate cohort based on completion date
    ) |> 
  relocate(Random_ID, cohort)                                              


sa |> mutate(uni = as_label(as_numeric(uni))) |> 
  filter(email != "",) |> 
  group_by(uni, cohort) |> 
  count(followup) |> 
  print(n = 100)                                                            # 66 of cohort 2 agreed


#### ---- ISSUES ---- ##########################################################

## Case duplicates (by email)

sa |> 
  janitor::get_dupes(email) |> 
  select(email, dupe_count, Random_ID, StartDate) |> 
  print()

sa |> 
  janitor::get_dupes(IPAddress) |> 
  select(email, IPAddress, dupe_count, Random_ID, StartDate) |> 
  print()


### Will delete the two later responses

sa <- sa |> 
  filter(!Random_ID %in% c("8436", "8175"))



### Select out meta and safeguarded variables ----------------------------------

sa_safe <- sa |> 
  select(Status:Progress, Finished:UserLanguage, followup, email, Random_ID) 

sa <- sa |> 
  select(!c(StartDate, EndDate, Status, IPAddress, Progress, RecordedDate:UserLanguage, email, followup))

Analysis data

Click to see code 
sa <- sa |>
  filter(Finished == "True")                                    # keep only finished cases

For the analysis, we keep only the finished surveys, dropping incomplete cases. We also check for any columns with all missing values and find three variables (proglength_txt, sib3occ_study_txt, sib4occ_study_txt), which we delete.

The analysis dataset now contains 141 cases/rows and 169 variables/columns. 105 responses are from York St John University students.

We check for missing responses for each respondent, and find that each respondent in the analysis dataset has a minimum of 11 and maximum of 21 missing responses, witha median of 16.

Click to see code 
sa <- datawizard::remove_empty_columns(sa)

sa <- sa |> 
  rowwise() |> 
  mutate(n_NAs = sum(is.na(across(everything()))))

summary(sa$n_NAs)

We export the analysis dataset with the name sa2020 in SPSS .sav format in a new folder data_in.

Click to see code 
## Save

fs::dir_create("data_in")
write_spss(sa, "data_in/sa2020.sav")

Variable documentation

Click to see code 
rm(list = ls())

sa <- read_spss("data_in/sa2020.sav")
View codebook for numeric and categorical variables
Click to see code 
`MAXOUT Study Abroad - YSJ 2020 - Codebook` <- sa


`MAXOUT Study Abroad - YSJ 2020 - Codebook` |>
    select(!contains("_txt")) |> 
    data_codebook(variable_label_width = 70, 
                  value_label_width = 60,
                  max_values = 10,
                  range_at = 5) |> 
    print_html(font_size = "70%",
               line_padding = 0)
select(`MAXOUT Study Abroad - YSJ 2020 - Codebook`, !contains("_txt")) (141 rows and 136 variables, 136 shown)
ID Name Label Type Missings Values Value Labels N
1 Random_ID character 0 (0.0%) 1038 1 (0.7%)
1074 1 (0.7%)
1129 1 (0.7%)
1286 1 (0.7%)
1313 1 (0.7%)
1412 1 (0.7%)
1475 1 (0.7%)
1508 1 (0.7%)
1512 1 (0.7%)
1521 1 (0.7%)
(...)
2 cohort character 0 (0.0%) 2019/2020 70 (49.6%)
2020/2021 71 (50.4%)
3 Duration Duration (in seconds) numeric 0 (0.0%) [553, 20039] 141
4 Finished Finished categorical 0 (0.0%) 2 True 141 (100.0%)
5 uni University categorical 0 (0.0%) 1 York St John University 105 (74.5%)
5 The University of Sheffield 8 (5.7%)
6 The University of Oxford 2 (1.4%)
14 The University of Birmingham 8 (5.7%)
17 Oxford Brookes University 5 (3.5%)
18 Newcastle University 6 (4.3%)
21 Cardiff University 7 (5.0%)
6 language Main language categorical 0 (0.0%) 1 Japanese 79 (56.0%)
2 Korean 62 (44.0%)
7 proglength How long is your programme of study? categorical 0 (0.0%) 1 3 years 9 (6.4%)
2 4 years 132 (93.6%)
8 studyr Which year are you currently in? categorical 0 (0.0%) 1 1st year 118 (83.7%)
2 2nd year 22 (15.6%)
3 Other 1 (0.7%)
9 sa Does the programme have a Study Abroad year/semester? categorical 0 (0.0%) 1 Yes 141 (100.0%)
10 sayr In which academic year do you expect to go on a Study Abroad year? categorical 0 (0.0%) 1 2020/2021 32 (22.7%)
2 2021/2022 38 (27.0%)
3 2022/2023 71 (50.4%)
11 course_reason_knowl Study choice - Prior knowledge of JP/KO categorical 0 (0.0%) 1 Not at all 23 (16.3%)
2 To some extent 82 (58.2%)
3 Very much 36 (25.5%)
12 course_reason_lang Study choice - Desire to learn JP/KO categorical 0 (0.0%) 2 To some extent 6 (4.3%)
3 Very much 135 (95.7%)
13 course_reason_cult Study choice - Desire to learn about JP/KO culture categorical 0 (0.0%) 1 Not at all 3 (2.1%)
2 To some extent 14 (9.9%)
3 Very much 124 (87.9%)
14 course_reason_family Study choice - I have family ties to JP/KO categorical 0 (0.0%) 1 Not at all 132 (93.6%)
2 To some extent 4 (2.8%)
3 Very much 5 (3.5%)
15 course_reason_friends Study choice - I had friends from JP/KO categorical 0 (0.0%) 1 Not at all 95 (67.4%)
2 To some extent 26 (18.4%)
3 Very much 20 (14.2%)
16 course_reason_romance Study choice - I had a romantic relationship with someone from JP/KO categorical 0 (0.0%) 1 Not at all 130 (92.2%)
2 To some extent 7 (5.0%)
3 Very much 4 (2.8%)
17 course_reason_wantromance Study choice - Desire to have a romantic relationship with someone categorical 0 (0.0%) 1 Not at all 105 (74.5%)
from JP/KO 2 To some extent 30 (21.3%)
3 Very much 6 (4.3%)
18 course_reason_career Study choice - Future career opportunities in JP/KO categorical 0 (0.0%) 1 Not at all 1 (0.7%)
2 To some extent 33 (23.4%)
3 Very much 107 (75.9%)
19 course_reason_move Study choice - Desire to live long-term in JP/KO in the future categorical 0 (0.0%) 1 Not at all 10 (7.1%)
2 To some extent 49 (34.8%)
3 Very much 82 (58.2%)
20 course_reason_SA Study choice - The opportunity to visit JP/KO as part of Study Abroad categorical 0 (0.0%) 1 Not at all 2 (1.4%)
2 To some extent 18 (12.8%)
3 Very much 121 (85.8%)
21 course_reason_money Study choice - High earning potential after graduation categorical 0 (0.0%) 1 Not at all 21 (14.9%)
2 To some extent 62 (44.0%)
3 Very much 58 (41.1%)
22 course_reason_other Study choice - Other categorical 2 (1.4%) 1 Not at all 121 (87.1%)
2 To some extent 11 (7.9%)
3 Very much 7 (5.0%)
23 works Do you work besides your studies? categorical 0 (0.0%) 1 Yes 34 (24.1%)
2 No 107 (75.9%)
24 pressure Do you feel any pressure related to achieving a certain proficiency categorical 0 (0.0%) 1 Yes 95 (67.4%)
in JP/KO? 2 No 46 (32.6%)
25 optionals Would like to do optional assignments to improve my JP/KO proficiency categorical 0 (0.0%) 1 Strongly disagree 1 (0.7%)
2 Disagree 3 (2.1%)
3 Somewhat disagree 1 (0.7%)
4 Somewhat agree 25 (17.7%)
5 Agree 58 (41.1%)
6 Strongly agree 53 (37.6%)
26 likestudy I like to spend lots of time studying JP/KO categorical 0 (0.0%) 1 Strongly disagree 2 (1.4%)
2 Disagree 3 (2.1%)
3 Somewhat disagree 2 (1.4%)
4 Somewhat agree 26 (18.4%)
5 Agree 60 (42.6%)
6 Strongly agree 48 (34.0%)
27 likemore I like to concentrate on studying JP/KO more than any other topic categorical 0 (0.0%) 1 Strongly disagree 2 (1.4%)
2 Disagree 3 (2.1%)
3 Somewhat disagree 5 (3.5%)
4 Somewhat agree 20 (14.2%)
5 Agree 37 (26.2%)
6 Strongly agree 74 (52.5%)
28 doingbest I think I am doing my best to learn JP/KO categorical 0 (0.0%) 1 Strongly disagree 1 (0.7%)
2 Disagree 1 (0.7%)
3 Somewhat disagree 11 (7.8%)
4 Somewhat agree 38 (27.0%)
5 Agree 61 (43.3%)
6 Strongly agree 29 (20.6%)
29 img_livdiscuss Can imagine living abroad and having a discussion in JP/KO categorical 1 (0.7%) 3 Somewhat disagree 2 (1.4%)
4 Somewhat agree 27 (19.3%)
5 Agree 50 (35.7%)
6 Strongly agree 61 (43.6%)
30 img_study Can imagine studying in university where all courses taught in JP/KO categorical 1 (0.7%) 1 Strongly disagree 4 (2.9%)
2 Disagree 9 (6.4%)
3 Somewhat disagree 11 (7.9%)
4 Somewhat agree 46 (32.9%)
5 Agree 39 (27.9%)
6 Strongly agree 31 (22.1%)
31 img_careerusing Whenever I think of my future career, I imagine myself using JP/KO categorical 0 (0.0%) 2 Disagree 2 (1.4%)
3 Somewhat disagree 7 (5.0%)
4 Somewhat agree 28 (19.9%)
5 Agree 37 (26.2%)
6 Strongly agree 67 (47.5%)
32 img_spkwfriends Can imagine speaking JP/KO with international friends or colleagues categorical 0 (0.0%) 4 Somewhat agree 19 (13.5%)
5 Agree 59 (41.8%)
6 Strongly agree 63 (44.7%)
33 img_spkwlocals Can imagine living abroad and using JP/KO effectively for com with categorical 1 (0.7%) 2 Disagree 1 (0.7%)
locals 3 Somewhat disagree 3 (2.1%)
4 Somewhat agree 16 (11.4%)
5 Agree 57 (40.7%)
6 Strongly agree 63 (45.0%)
34 img_spknative I can imagine myself speaking JP/KO as if I were a native speaker of categorical 0 (0.0%) 1 Strongly disagree 5 (3.5%)
JP/KO 2 Disagree 10 (7.1%)
3 Somewhat disagree 19 (13.5%)
4 Somewhat agree 43 (30.5%)
5 Agree 36 (25.5%)
6 Strongly agree 28 (19.9%)
35 img_write I can imagine myself writing e-mails/letters fluently in JP/KO categorical 0 (0.0%) 1 Strongly disagree 1 (0.7%)
2 Disagree 3 (2.1%)
3 Somewhat disagree 9 (6.4%)
4 Somewhat agree 34 (24.1%)
5 Agree 58 (41.1%)
6 Strongly agree 36 (25.5%)
36 futureneed The things I want to do in the future require me to use JP/KO categorical 0 (0.0%) 1 Strongly disagree 1 (0.7%)
2 Disagree 3 (2.1%)
3 Somewhat disagree 6 (4.3%)
4 Somewhat agree 32 (22.7%)
5 Agree 45 (31.9%)
6 Strongly agree 54 (38.3%)
37 friendsthink I study JP/KO because close friends of mine think it is important categorical 0 (0.0%) 1 Strongly disagree 73 (51.8%)
2 Disagree 40 (28.4%)
3 Somewhat disagree 13 (9.2%)
4 Somewhat agree 7 (5.0%)
5 Agree 4 (2.8%)
6 Strongly agree 4 (2.8%)
38 pplexpect Learning JP/KO necessary bc people surrounding me expect me to do so categorical 0 (0.0%) 1 Strongly disagree 83 (58.9%)
2 Disagree 30 (21.3%)
3 Somewhat disagree 12 (8.5%)
4 Somewhat agree 7 (5.0%)
5 Agree 3 (2.1%)
6 Strongly agree 6 (4.3%)
39 pplirespect Learning JP/KO important bc people I respect think I should do it categorical 0 (0.0%) 1 Strongly disagree 78 (55.3%)
2 Disagree 31 (22.0%)
3 Somewhat disagree 15 (10.6%)
4 Somewhat agree 7 (5.0%)
5 Agree 2 (1.4%)
6 Strongly agree 8 (5.7%)
40 respectmore Studying JP/KO to me bc other ppl will respect me more if I know categorical 0 (0.0%) 1 Strongly disagree 57 (40.4%)
JP/KO 2 Disagree 30 (21.3%)
3 Somewhat disagree 15 (10.6%)
4 Somewhat agree 22 (15.6%)
5 Agree 12 (8.5%)
6 Strongly agree 5 (3.5%)
41 prefplace Have preferred town/region to live while on SA categorical 0 (0.0%) 1 Yes 79 (56.0%)
2 No 62 (44.0%)
42 prefuni Have preferred university to study while on SA categorical 0 (0.0%) 1 Yes 37 (26.2%)
2 No 104 (73.8%)
43 concern_lang SA concern - Not being confident enough with the language categorical 0 (0.0%) 1 1 4 (2.8%)
2 2 10 (7.1%)
3 3 27 (19.1%)
4 4 35 (24.8%)
5 5 39 (27.7%)
6 6 26 (18.4%)
44 concern_cult SA concern - Wary of living in another country/culture categorical 0 (0.0%) 1 1 28 (19.9%)
2 2 34 (24.1%)
3 3 30 (21.3%)
4 4 26 (18.4%)
5 5 16 (11.3%)
6 6 7 (5.0%)
45 concern_money SA concern - Not being able to afford living costs categorical 0 (0.0%) 1 1 6 (4.3%)
2 2 11 (7.8%)
3 3 18 (12.8%)
4 4 33 (23.4%)
5 5 39 (27.7%)
6 6 34 (24.1%)
46 concern_studyexp SA concern - Different expectations/standards of study at the categorical 0 (0.0%) 1 1 5 (3.5%)
visiting university 2 2 13 (9.2%)
3 3 38 (27.0%)
4 4 38 (27.0%)
5 5 30 (21.3%)
6 6 17 (12.1%)
47 concern_parents SA concern - Being far away from parents categorical 0 (0.0%) 1 1 34 (24.1%)
2 2 25 (17.7%)
3 3 30 (21.3%)
4 4 22 (15.6%)
5 5 19 (13.5%)
6 6 10 (7.1%)
7 Does not apply 1 (0.7%)
48 concern_friends SA concern - Being far away from friends categorical 0 (0.0%) 1 1 27 (19.1%)
2 2 27 (19.1%)
3 3 36 (25.5%)
4 4 20 (14.2%)
5 5 19 (13.5%)
6 6 9 (6.4%)
7 Does not apply 3 (2.1%)
49 concern_partner SA concern - Being far away from partner categorical 0 (0.0%) 1 1 43 (30.5%)
2 2 6 (4.3%)
3 3 8 (5.7%)
4 4 6 (4.3%)
5 5 9 (6.4%)
6 6 7 (5.0%)
7 Does not apply 62 (44.0%)
50 plan_travelcnt Plan while on SA- Traveling around JP/KO categorical 0 (0.0%) 1 1 1 (0.7%)
2 2 3 (2.1%)
3 3 6 (4.3%)
4 4 19 (13.5%)
5 5 48 (34.0%)
6 6 64 (45.4%)
51 plan_travelreg Plan while on SA- Traveling around East Asia categorical 0 (0.0%) 1 1 15 (10.6%)
2 2 21 (14.9%)
3 3 29 (20.6%)
4 4 33 (23.4%)
5 5 24 (17.0%)
6 6 19 (13.5%)
52 plan_langlearn Plan while on SA- Learning JP/KO intensively categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 1 (0.7%)
3 3 6 (4.3%)
4 4 20 (14.2%)
5 5 34 (24.1%)
6 6 78 (55.3%)
53 plan_comloc Plan while on SA- Communicating with local people in JP/KO in categorical 0 (0.0%) 1 1 1 (0.7%)
everyday life 2 2 2 (1.4%)
3 3 2 (1.4%)
4 4 9 (6.4%)
5 5 37 (26.2%)
6 6 90 (63.8%)
54 plan_makefriends Plan while on SA- Making JP/KO friends categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 1 (0.7%)
3 3 4 (2.8%)
4 4 21 (14.9%)
5 5 45 (31.9%)
6 6 68 (48.2%)
55 plan_netw Plan while on SA- Expanding my global social network categorical 0 (0.0%) 1 1 7 (5.0%)
2 2 14 (9.9%)
3 3 24 (17.0%)
4 4 23 (16.3%)
5 5 35 (24.8%)
6 6 38 (27.0%)
56 plan_popcult Plan while on SA- Experiencing JP/KO popular culture categorical 0 (0.0%) 1 1 3 (2.1%)
2 2 3 (2.1%)
3 3 8 (5.7%)
4 4 20 (14.2%)
5 5 46 (32.6%)
6 6 61 (43.3%)
57 plan_jobprep Plan while on SA- Preparing myself for getting a good job in future categorical 0 (0.0%) 2 2 2 (1.4%)
3 3 8 (5.7%)
4 4 19 (13.5%)
5 5 33 (23.4%)
6 6 79 (56.0%)
58 plan_careerops Plan while on SA- Actively looking for career opportunities categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 9 (6.4%)
3 3 18 (12.8%)
4 4 28 (19.9%)
5 5 29 (20.6%)
6 6 55 (39.0%)
59 plan_attend Plan while on SA- Attending university in JP/KO as a full-time student categorical 0 (0.0%) 2 2 4 (2.8%)
3 3 5 (3.5%)
4 4 15 (10.6%)
5 5 39 (27.7%)
6 6 78 (55.3%)
60 plan_modules Plan while on SA- Taking modules that fit my own interests categorical 0 (0.0%) 2 2 4 (2.8%)
3 3 1 (0.7%)
4 4 19 (13.5%)
5 5 36 (25.5%)
6 6 81 (57.4%)
61 likely_travelcnt Likely succeed - Traveling around JP/KO categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 5 (3.5%)
3 3 17 (12.1%)
4 4 35 (24.8%)
5 5 37 (26.2%)
6 6 36 (25.5%)
7 I don't know 9 (6.4%)
62 likely_travelreg Likely succeed - Traveling around East Asia categorical 0 (0.0%) 1 1 33 (23.4%)
2 2 17 (12.1%)
3 3 30 (21.3%)
4 4 20 (14.2%)
5 5 10 (7.1%)
6 6 10 (7.1%)
7 I don't know 21 (14.9%)
63 likely_langlearn Likely succeed - Learning JP/KO intensively categorical 0 (0.0%) 2 2 1 (0.7%)
3 3 7 (5.0%)
4 4 24 (17.0%)
5 5 54 (38.3%)
6 6 47 (33.3%)
7 I don't know 8 (5.7%)
64 likely_comloc Likely succeed - Communicating with local people in JP/KO for categorical 0 (0.0%) 2 2 2 (1.4%)
everyday tasks 3 3 8 (5.7%)
4 4 22 (15.6%)
5 5 45 (31.9%)
6 6 57 (40.4%)
7 I don't know 7 (5.0%)
65 likely_makefriends Likely succeed - Making JP/KO friends categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 6 (4.3%)
3 3 17 (12.1%)
4 4 33 (23.4%)
5 5 43 (30.5%)
6 6 31 (22.0%)
7 I don't know 9 (6.4%)
66 likely_netw Likely succeed - Expanding my global social network categorical 0 (0.0%) 1 1 11 (7.8%)
2 2 14 (9.9%)
3 3 21 (14.9%)
4 4 33 (23.4%)
5 5 33 (23.4%)
6 6 16 (11.3%)
7 I don't know 13 (9.2%)
67 likely_popcult Likely succeed - Experiencing JP/KO popular culture categorical 0 (0.0%) 2 2 2 (1.4%)
3 3 5 (3.5%)
4 4 19 (13.5%)
5 5 47 (33.3%)
6 6 61 (43.3%)
7 I don't know 7 (5.0%)
68 likely_jobprep Likely succeed - Preparing myself for getting a good job in the future categorical 0 (0.0%) 2 2 5 (3.5%)
3 3 24 (17.0%)
4 4 44 (31.2%)
5 5 40 (28.4%)
6 6 18 (12.8%)
7 I don't know 10 (7.1%)
69 likely_careerops Likely succeed - Actively looking for career opportunities categorical 1 (0.7%) 1 1 8 (5.7%)
2 2 12 (8.6%)
3 3 22 (15.7%)
4 4 37 (26.4%)
5 5 30 (21.4%)
6 6 19 (13.6%)
7 I don't know 12 (8.6%)
70 likely_attend Likely succeed - Attending university in JP/KO as a full-time student categorical 0 (0.0%) 1 1 1 (0.7%)
2 2 2 (1.4%)
3 3 6 (4.3%)
4 4 14 (9.9%)
5 5 38 (27.0%)
6 6 70 (49.6%)
7 I don't know 10 (7.1%)
71 likely_modules Likely succeed - Taking modules that fit my own interests categorical 0 (0.0%) 1 1 1 (0.7%)
2 2 3 (2.1%)
3 3 8 (5.7%)
4 4 24 (17.0%)
5 5 53 (37.6%)
6 6 42 (29.8%)
7 I don't know 10 (7.1%)
72 expect_socialise Who do you expect to socialize with most while on Study Abroad? categorical 0 (0.0%) 1 Mainly with people/colleagues from JP/KO 54 (38.3%)
2 Mainly with friends/colleagues from my UK university 22 (15.6%)
3 Mainly with other foreign students 21 (14.9%)
4 Mainly with students from English speaking countries 3 (2.1%)
5 I don't know 41 (29.1%)
73 expsa_knowother Expect SA worthwhile for - Knowledge and understanding of another categorical 0 (0.0%) 2 2 1 (0.7%)
country 4 4 8 (5.7%)
5 5 27 (19.1%)
6 6 105 (74.5%)
74 expsa_matur Expect SA worthwhile for - Maturity and personal development categorical 0 (0.0%) 2 2 1 (0.7%)
3 3 3 (2.1%)
4 4 9 (6.4%)
5 5 35 (24.8%)
6 6 93 (66.0%)
75 expsa_rethinkhome Expect SA worthwhile for - New ways of thinking about my home country categorical 0 (0.0%) 1 1 2 (1.4%)
2 2 6 (4.3%)
3 3 15 (10.6%)
4 4 28 (19.9%)
5 5 26 (18.4%)
6 6 64 (45.4%)
76 expsa_other Expect SA worthwhile for - Something else categorical 17 (12.1%) 1 1 83 (66.9%)
2 2 2 (1.6%)
3 3 8 (6.5%)
4 4 6 (4.8%)
5 5 7 (5.6%)
6 6 18 (14.5%)
77 satolive SA as a stepping stone towards living abroad after graduation? categorical 0 (0.0%) 1 Yes 126 (89.4%)
2 No 1 (0.7%)
3 Don't know 14 (9.9%)
78 beenbefore Been in JP/KO before categorical 0 (0.0%) 1 Yes 33 (23.4%)
2 No 108 (76.6%)
79 friends Number of JP/KO friends categorical 0 (0.0%) 1 None 76 (53.9%)
2 One 14 (9.9%)
3 Two 15 (10.6%)
4 Three 5 (3.5%)
5 More than three 31 (22.0%)
80 friendsconnect Number of JP/KO friends/acquaint on online social media categorical 0 (0.0%) 1 None 57 (40.4%)
2 Fewer than 5 45 (31.9%)
3 Between 5 and 10 18 (12.8%)
4 Between 10 and 50 18 (12.8%)
5 More than 50 3 (2.1%)
81 comfreq How often communicate with least one JP/KO friend/acquaintance categorical 56 (39.7%) 1 Every day 14 (16.5%)
2 At least once a week 21 (24.7%)
3 At least once a month 24 (28.2%)
4 Several times a year 13 (15.3%)
5 At most once a year 13 (15.3%)
82 comengl Speaks with JP/KO friends in English categorical 69 (48.9%) 1 English 72 (100.0%)
83 comjpko Speaks with JP/KO friends in JP/KO categorical 89 (63.1%) 1 JP/KO 52 (100.0%)
84 comanother Speaks with JP/KO friends in Another language categorical 140 (99.3%) 1 Another language 1 (100.0%)
85 cntlived Countries lived in more than 3 months (incl. COB) categorical 0 (0.0%) 1 One 102 (72.3%)
2 Two 32 (22.7%)
3 Three 5 (3.5%)
4 Four 1 (0.7%)
6 More than five 1 (0.7%)
86 childtravel How often did you travel abroad with your parents/carers as a child categorical 0 (0.0%) 1 Never 27 (19.1%)
or teenager? 2 Once or twice 49 (34.8%)
3 Every year 54 (38.3%)
4 Several times a year 11 (7.8%)
87 otherlang Do you speak any other language apart from English and JP/KO? categorical 0 (0.0%) 1 Yes 57 (40.4%)
2 No 84 (59.6%)
88 parotherlang Parents/caregivers speak any lang other than English/native language? categorical 0 (0.0%) 1 Yes, one of my parents / caregivers 24 (17.0%)
2 Yes, both my parents / caregivers 16 (11.3%)
3 No 101 (71.6%)
89 imp_alike How important to me - The similarity I share with others in my categorical 0 (0.0%) 1 1 9 (6.4%)
group(s) 2 2 13 (9.2%)
3 3 33 (23.4%)
4 4 50 (35.5%)
5 5 32 (22.7%)
6 6 4 (2.8%)
90 imp_rebel How important to me - My rebelliousness categorical 0 (0.0%) 1 1 59 (41.8%)
2 2 35 (24.8%)
3 3 19 (13.5%)
4 4 18 (12.8%)
5 5 9 (6.4%)
6 6 1 (0.7%)
91 imp_nat How important to me - My nationality or nationalities categorical 0 (0.0%) 1 1 39 (27.7%)
2 2 25 (17.7%)
3 3 31 (22.0%)
4 4 26 (18.4%)
5 5 11 (7.8%)
6 6 9 (6.4%)
92 imp_unique How important to me - Need to be compl distinct and unique from categorical 0 (0.0%) 1 1 43 (30.5%)
everyone 2 2 35 (24.8%)
3 3 25 (17.7%)
4 4 19 (13.5%)
5 5 16 (11.3%)
6 6 3 (2.1%)
93 imp_belong How important to me - The memberships I have in various groups categorical 0 (0.0%) 1 1 41 (29.1%)
2 2 34 (24.1%)
3 3 33 (23.4%)
4 4 26 (18.4%)
5 5 6 (4.3%)
6 6 1 (0.7%)
94 imp_creative How important to me - My creativity categorical 0 (0.0%) 1 1 4 (2.8%)
2 2 9 (6.4%)
3 3 20 (14.2%)
4 4 34 (24.1%)
5 5 40 (28.4%)
6 6 34 (24.1%)
95 imp_lived How important to me - The places where I have lived categorical 0 (0.0%) 1 1 48 (34.0%)
2 2 31 (22.0%)
3 3 18 (12.8%)
4 4 22 (15.6%)
5 5 13 (9.2%)
6 6 9 (6.4%)
96 imp_difference How important to me - My sense of being different from others categorical 0 (0.0%) 1 1 31 (22.0%)
2 2 21 (14.9%)
3 3 28 (19.9%)
4 4 35 (24.8%)
5 5 19 (13.5%)
6 6 7 (5.0%)
97 imp_ethnic How important to me - My sense of belonging to my own ethnic/racial categorical 0 (0.0%) 1 1 61 (43.3%)
group 2 2 27 (19.1%)
3 3 21 (14.9%)
4 4 18 (12.8%)
5 5 8 (5.7%)
6 6 6 (4.3%)
98 imp_individual How important to me - My complete individuality categorical 0 (0.0%) 1 1 13 (9.2%)
2 2 13 (9.2%)
3 3 30 (21.3%)
4 4 35 (24.8%)
5 5 31 (22.0%)
6 6 19 (13.5%)
99 imp_gender How important to me - My gender group categorical 0 (0.0%) 1 1 62 (44.0%)
2 2 22 (15.6%)
3 3 18 (12.8%)
4 4 14 (9.9%)
5 5 18 (12.8%)
6 6 7 (5.0%)
100 imp_boldness How important to me - My boldness categorical 0 (0.0%) 1 1 39 (27.7%)
2 2 19 (13.5%)
3 3 25 (17.7%)
4 4 42 (29.8%)
5 5 14 (9.9%)
6 6 2 (1.4%)
101 imp_skin How important to me - The colour of my skin categorical 0 (0.0%) 1 1 94 (66.7%)
2 2 19 (13.5%)
3 3 12 (8.5%)
4 4 8 (5.7%)
5 5 6 (4.3%)
6 6 2 (1.4%)
102 imp_nonconform How important to me - My nonconformity categorical 0 (0.0%) 1 1 50 (35.5%)
2 2 25 (17.7%)
3 3 27 (19.1%)
4 4 20 (14.2%)
5 5 13 (9.2%)
6 6 6 (4.3%)
103 imp_nativelang How important to me - My native language categorical 1 (0.7%) 1 1 38 (27.1%)
2 2 15 (10.7%)
3 3 31 (22.1%)
4 4 35 (25.0%)
5 5 12 (8.6%)
6 6 9 (6.4%)
104 imp_independence How important to me - My sense of independence from others categorical 0 (0.0%) 1 1 15 (10.6%)
2 2 9 (6.4%)
3 3 31 (22.0%)
4 4 41 (29.1%)
5 5 31 (22.0%)
6 6 14 (9.9%)
105 imp_political How important to me - My political beliefs categorical 0 (0.0%) 1 1 41 (29.1%)
2 2 20 (14.2%)
3 3 31 (22.0%)
4 4 15 (10.6%)
5 5 26 (18.4%)
6 6 8 (5.7%)
106 imp_education How important to me - My level of education categorical 0 (0.0%) 1 1 24 (17.0%)
2 2 27 (19.1%)
3 3 26 (18.4%)
4 4 26 (18.4%)
5 5 28 (19.9%)
6 6 10 (7.1%)
107 imp_career How important to me - My future career categorical 0 (0.0%) 1 1 18 (12.8%)
2 2 18 (12.8%)
3 3 13 (9.2%)
4 4 31 (22.0%)
5 5 31 (22.0%)
6 6 30 (21.3%)
108 imp_langcom How important to me - Sense belonging to a community of JP/KO categorical 0 (0.0%) 1 1 16 (11.3%)
speakers 2 2 17 (12.1%)
3 3 29 (20.6%)
4 4 36 (25.5%)
5 5 27 (19.1%)
6 6 16 (11.3%)
109 gender What is your gender? categorical 0 (0.0%) 1 Male 39 (27.7%)
2 Female 93 (66.0%)
3 Other 8 (5.7%)
4 Prefer not to say 1 (0.7%)
110 age What is your age? categorical 0 (0.0%) 1 18 29 (20.6%)
2 19 42 (29.8%)
3 20 29 (20.6%)
4 21 12 (8.5%)
5 22 7 (5.0%)
6 23 4 (2.8%)
7 24 4 (2.8%)
8 25 2 (1.4%)
9 26 3 (2.1%)
10 27 3 (2.1%)
(...) (...)
111 finishedschool In what year did you finish your secondary/compulsory education? categorical 2 (1.4%) 1 2019 45 (32.4%)
2 2018 39 (28.1%)
3 2017 17 (12.2%)
4 2016 12 (8.6%)
5 2015 7 (5.0%)
6 2014 1 (0.7%)
7 2013 3 (2.2%)
8 2012 3 (2.2%)
9 2011 3 (2.2%)
10 2010 1 (0.7%)
(...) (...)
112 gapyear Went uni immediately after finishing secondary/compulsory education categorical 0 (0.0%) 1 Yes 72 (51.1%)
2 No 69 (48.9%)
113 gapyear_work After school I got a paid job categorical 105 (74.5%) 1 I got a paid job 36 (100.0%)
114 gapyear_apprentice After school I did an apprenticeship categorical 136 (96.5%) 1 I did an apprenticeship 5 (100.0%)
115 gapyear_travel After school I travelled categorical 133 (94.3%) 1 I travelled 8 (100.0%)
116 gapyear_carer After school I cared for someone (e.g. child, parents or others) categorical 137 (97.2%) 1 I cared for someone (e.g. child, parents or others) 4 (100.0%)
117 gapyear_other After school I did something else categorical 113 (80.1%) 1 I did something else 28 (100.0%)
118 intstudnt Are you an international student in the UK? categorical 0 (0.0%) 1 Yes 14 (9.9%)
2 No 127 (90.1%)
119 bornuk Were you born in the UK? categorical 0 (0.0%) 1 Yes 113 (80.1%)
2 No 28 (19.9%)
120 pargrad Do your parents/caregivers have university-level education? categorical 0 (0.0%) 1 Yes, one of my parents / caregivers 42 (29.8%)
2 Yes, both of my parents / caregivers 27 (19.1%)
3 No 72 (51.1%)
121 school_statecomp School type State comprehensive categorical 46 (32.6%) 1 State comprehensive 95 (100.0%)
122 school_grammar School type Grammar school categorical 132 (93.6%) 1 Grammar school 9 (100.0%)
123 school_statesixth School type State sixth-form college categorical 74 (52.5%) 1 State sixth-form college 67 (100.0%)
124 school_private School type Private (feepaying) schools categorical 134 (95.0%) 1 Private (feepaying) schools 7 (100.0%)
125 school_intl School type International school (in UK) categorical 140 (99.3%) 1 International school (in UK) 1 (100.0%)
126 school_abroad School type Schooling abroad categorical 129 (91.5%) 1 Schooling abroad 12 (100.0%)
127 school_other School type Other categorical 125 (88.7%) 1 Other 16 (100.0%)
128 freemeals While you were at school, did you ever receive free school meals? categorical 0 (0.0%) 1 Yes 35 (24.8%)
2 No 106 (75.2%)
129 postcode What was your home postcode during your last year at school? character 0 (0.0%) 3 (2.1%)
00166 1 (0.7%)
077191 1 (0.7%)
1014. 1 (0.7%)
1102. 1 (0.7%)
30132 1 (0.7%)
400004 1 (0.7%)
4003. 1 (0.7%)
547530 1 (0.7%)
66-100 1 (0.7%)
(...)
130 nsiblings How many siblings do you have? categorical 0 (0.0%) 1 None 15 (10.6%)
2 One 70 (49.6%)
3 Two 33 (23.4%)
4 Three 11 (7.8%)
5 Four 5 (3.5%)
6 More than four 7 (5.0%)
131 sibocc Primary occupation of sibling in the past 12 months? categorical 72 (51.1%) 1 S/he was at school 27 (39.1%)
2 S/he was a university student 12 (17.4%)
3 S/he was employed 21 (30.4%)
4 S/he was self-employed / business owner 1 (1.4%)
5 S/he was a jobseeker / unemployed 6 (8.7%)
6 Something else 2 (2.9%)
132 sib1occ Primary occupation of oldest sibling in the past 12 months? categorical 85 (60.3%) 1 S/he was at school 11 (19.6%)
2 S/he was a university student 8 (14.3%)
3 S/he was employed 16 (28.6%)
4 S/he was self-employed / business owner 6 (10.7%)
5 S/he was a jobseeker / unemployed 9 (16.1%)
6 Something else 6 (10.7%)
133 sib2occ Primary occupation of second oldest sibling in the past 12 months? categorical 86 (61.0%) 1 S/he was at school 29 (52.7%)
2 S/he was a university student 6 (10.9%)
3 S/he was employed 11 (20.0%)
4 S/he was self-employed / business owner 2 (3.6%)
5 S/he was a jobseeker / unemployed 4 (7.3%)
6 Something else 3 (5.5%)
134 sib3occ Primary occupation of third oldest sibling in the past 12 months? categorical 118 (83.7%) 1 S/he was at school 13 (56.5%)
3 S/he was employed 3 (13.0%)
4 S/he was self-employed / business owner 1 (4.3%)
5 S/he was a jobseeker / unemployed 2 (8.7%)
6 Something else 4 (17.4%)
135 sib4occ Primary occupation of fourth oldest sibling in the past 12 months? categorical 129 (91.5%) 1 S/he was at school 5 (41.7%)
3 S/he was employed 1 (8.3%)
5 S/he was a jobseeker / unemployed 3 (25.0%)
6 Something else 3 (25.0%)
136 n_NAs numeric 0 (0.0%) [11, 21] 141
View codebook for string/text variables
Click to see code 
`MAXOUT Study Abroad - YSJ 2020 - Codebook` |>
    select(contains("_txt")) |> 
    data_codebook(variable_label_width = 70, 
                  value_label_width = 60,
                  max_values = 10,
                  range_at = 5) |> 
    print_html(font_size = "70%",
               line_padding = 0)
select(`MAXOUT Study Abroad - YSJ 2020 - Codebook`, contains("_txt")) (141 rows and 31 variables, 31 shown)
ID Name Label Type Missings Values N
1 course_txt Course character 0 (0.0%) BA Anthropology and Japanese Studies 1 (0.7%)
BA French and Japanese 1 (0.7%)
BA Hons Japanese, Linguistics & Tesol 1 (0.7%)
BA Hons, Modern Languages and Business Studies 1 (0.7%)
BA Italian and Japanese 1 (0.7%)
BA japanese 1 (0.7%)
BA Japanese 1 (0.7%)
BA Japanese and TESOL 2 (1.4%)
BA Japanese and Translation Studies 1 (0.7%)
BA Japanese Studies 3 (2.1%)
(...)
2 studyr_txt Please specify: character 0 (0.0%) 140 (99.3%)
3rd year, abroad scheme 1 (0.7%)
3 course_choice_txt Why did you choose to study JP/KO at university? character 0 (0.0%) After I went travelling, I realised my passion was being abroad so it only made sense to study a language. I was especially interested in Korea because I like the culture and have many friends in Korea. 1 (0.7%)
Always been intrested in Japanese culture, I also had a lot of life skills but didnt have a secondary language so I decided to go for it. 1 (0.7%)
Always been passionate about Japanese culture in general. Looking to live in Japan someday and get into teaching. 1 (0.7%)
At first as a teenager I was interested in pop culture such as jrock and anime but as I got older I also wanted to be able to learn about different parts ofJapanese culture and interact with people. For example, I'd like to be able to read literature and draw my own conclusions. 1 (0.7%)
Because i have been greatly interested in japanese and japan ever since i was a child 1 (0.7%)
because I love Japan, the culture, the people, the pop culture and everything else 1 (0.7%)
Because I started learning about Korean culture through k-pop and k-dramas and wanted to learn more about the culture. 1 (0.7%)
Because I’m deeply interested in Korean culture and I would like to have a career in teaching abroad in Korean in the future. 1 (0.7%)
Because of family ties and long term ongoing interest in the different culture, way of life and language 1 (0.7%)
Because of the opportunity of the study abroad year. 1 (0.7%)
(...)
4 uni_choice_txt Why did you choose the university where you currently study? character 0 (0.0%) After I visited the languages department at Cardiff university on the open day I knew instantly that this was the university for me. I just loved the warm and friendly atmosphere of the department. It wasn’t too big, and the staff and students that I interacted with were very down to earth. I could just picture myself studying there. Thus, without a doubt I chose Cardiff as my first choice and cannot imagine studying anywhere else. 1 (0.7%)
Because I heard the university was good for languages 1 (0.7%)
Because I was happy with the course detail they university provided and because it is not too far from home as well. 1 (0.7%)
Because it is the best course suited for me, location and course wise. 1 (0.7%)
Because it offered a 3 year programme which included a year of study abroad, the reduction of study abroad fees was also a big factor as I've always struggled with finances. 1 (0.7%)
Because it was the closest one to my hometown that allowed me to study Japanese at the same time as Linguistics. Also, I had seen that Newcastle had good quality language courses. 1 (0.7%)
Because of the city. 1 (0.7%)
Because of the city. York looked very attractive as it had the perfect mix of a busy city with history weaving through. My relatives call it the village-city. 1 (0.7%)
because staff seemed super friendly 1 (0.7%)
Because the expectation was that you go to Oxford or Cambridge if you can get in (this proved to be a big mistake), and Oxford supposedly had better accommodations for mental health, though in practice I can't imagine it being much worse. 1 (0.7%)
(...)
5 course_reason_other_txt If other factors contributed to your choice of study, please detail: character 0 (0.0%) 127 (90.1%)
After choosing to study Japanese I've developed a love for the language and I'm excited to learn about the country by living there, however before choosing I could have gone with any language and enjoyed it, the choice was more based on learning anything for the benefits of learning in itself. 1 (0.7%)
Having a degree opens up so many opportunities for people and can be a valuable investment. I wanted to work hard at something that I am actually interested in and enjoy in order to start my career, rather than wasting my life working a job that offers me no joy or progression opportunities. 1 (0.7%)
I feel like learning a second language, any language, is a huge skill and just an all around great interest to have. I find it very interesting. 1 (0.7%)
I wanted to study a language that was different from other langauges. 1 (0.7%)
I’m sick of rainy England and the people in it. A change of scenery on the other side of the world, as far away as possible, sounds great. 1 (0.7%)
Interest in the language system especially the complicated writing system. 1 (0.7%)
Interest in various forms of media that come from Japan - Games, Music, TV, Film, Youtube 1 (0.7%)
Japanese is fun for me 1 (0.7%)
Korean is becoming a lot more popular these days so I belive in the future there will be a lot of opportunities with being apble to speak korean worldwide 1 (0.7%)
(...)
6 student_job_txt What is your current job? character 0 (0.0%) 107 (75.9%)
Barista 2 (1.4%)
Bartender 1 (0.7%)
Customer assistant (part-time) 1 (0.7%)
Customer assistant in boots pharmacy. 1 (0.7%)
Customer Service Assistant 1 (0.7%)
Customer Service Assistant at my local CO-OP. 1 (0.7%)
Fraud Investigations Unit at Monzo Bank 1 (0.7%)
Freelance artist 1 (0.7%)
Freelancer with digital drawing 1 (0.7%)
(...)
7 career_hope_txt What career path do you hope to follow after graduation? character 0 (0.0%) A translator or an English teacher in South Korea. 1 (0.7%)
Actress/director/scriptwriter 1 (0.7%)
An English teacher in Japan or a translator. 1 (0.7%)
anything in Japan, games industry or graphic design would be fun 1 (0.7%)
At the moment I want to keep my options open 1 (0.7%)
Become a diplomat, be japamese teacher, create a school that would be based on japanese education system in Europe. 1 (0.7%)
Become an English teacher in Korea 1 (0.7%)
Becoming an english teacher to teach children a second language 1 (0.7%)
Classic/General Literature Translation 1 (0.7%)
Diplomacy and International Relations 1 (0.7%)
(...)
8 langprof_plan_txt What would you like to do with the achieved JP/KO proficiency? character 0 (0.0%) A master programme in South Korea 1 (0.7%)
Able to communicate fluently in Korean in my job. 1 (0.7%)
Apply for the JET program, do the 4 years in Japan, then work my way on staying there permenantly. 1 (0.7%)
As strange as it sounds I would probably start creating YouTube videos while working out my next steps with my proficiency. Pass on knowledge through video format in an accessible way. 1 (0.7%)
Be a diplomat, work in Japan, teach others Japanese 1 (0.7%)
Be a series,movie or book translator. 1 (0.7%)
Be able to communicate coherently in Korea as I hope to live there in the long term. 1 (0.7%)
Be able to get a job in Korea, or elsewhere, that requires fluent English and Korean language skills. Or, alternatively, study at a postgraduate level, on an appropriate postgrad programme that utilises the achieved Korean proficiency. 1 (0.7%)
be able to hold conversation with natives and build up strong friendships using Japanese as the main language spoken. I would also like my children in the future to speak Japanese and i hope to help them. 1 (0.7%)
Be able to live in Japan and communicate with ease in the workplace 1 (0.7%)
(...)
9 whatpressure_txt What pressure do you feel? character 0 (0.0%) 46 (32.6%)
to attain a good level, to have good pronunciation and grammar and also other things such as handwriting. 1 (0.7%)
A lot of the jobs I would like to aim for, look for near native Japanese. I am trying my best, but I feel being near native speaking japanese is something I may never achieve. 1 (0.7%)
At the end of the degree we are expected to be at a certain JLPT level (I believe N4), but many students are aiming for N3 or better, and so I feel pressured to achieve a higher proficiency than is expected of me. 1 (0.7%)
Can't explain it 1 (0.7%)
Even though I love it, I struggle to learn Japanese and feel pressure to carry on 1 (0.7%)
Expectation to instantly pick it up and be completely confident / achieving aims easily (i.e. exams, conversations...) 1 (0.7%)
Expectations 1 (0.7%)
Having only studied Japanese for two years I do worry that my language skills won’t be good enough during my year abroad 1 (0.7%)
Having previous knowledge to Japanese, I feel that I have pressure in attaining a high level of proficiency at the end of my degree. 1 (0.7%)
(...)
10 pressurefrom_txt Where do you feel that pressure is coming from? character 0 (0.0%) 47 (33.3%)
100% myself 1 (0.7%)
100% pressure from myself 1 (0.7%)
A bit of everything. I pick up the basics of a language really quickly so people expect the same rate throughout the language learning process. I’m hard on myself because I know I’m capable of it but my brain gets distracted really easily and chucks out necessary information, mistaking it for junk. My parents didn’t want me to do a korean degree but I told them people who have a second language are most likely to get the job and a better job at that. I want to move to Korea so I need to be fluent. My tutors have seen my work and the understanding I have of the language so far and expect me to keep it up but I’m struggling, especially recently, to learn vocabulary. 1 (0.7%)
All from myself as it’s such a huge part of my future career plans 1 (0.7%)
All the pressure is coming from myself. 1 (0.7%)
Both myself and future career plans 1 (0.7%)
Definitely from myself as I always push high standards on myself, but I also want to make my teachers proud and show them the hard work they've put into teaching me has paid off 1 (0.7%)
Definitely myself, I’ve set myself a goal that I really wish to achieve. 1 (0.7%)
Definitely the pressure is coming from myself. At times it can feel like it is coming from others, but that feeling is usually a projection of my own fears and expectations. 1 (0.7%)
(...)
11 prefplace_txt Preferred town/region while on SA character 0 (0.0%) 62 (44.0%)
A more rural area 1 (0.7%)
Busan 3 (2.1%)
Either Busan or Seoul 1 (0.7%)
Either Seoul, Busan or in the middle of nowhere. 1 (0.7%)
Every since I was a child I have always wanted to visit Tokyo so anywhere in Tokyo (if it is okay) 1 (0.7%)
Hokkaido 3 (2.1%)
Hokkaido or Tokyo or Okinawa 1 (0.7%)
Hokkaido or Touhoku 1 (0.7%)
Hokkaido, or any other rural place and hopefully cooler place. 1 (0.7%)
(...)
12 prefplace_reason_txt Why do you want to live there? character 0 (0.0%) 63 (44.7%)
Based on the research I did on various universities in Japan 1 (0.7%)
Because I have already been there and I know the city a little bit better than other cities and I really like it 1 (0.7%)
Because I love cities 1 (0.7%)
Because I would like to know the city. 1 (0.7%)
Because it gives me more knowledge of my surroundings 1 (0.7%)
Because it would benefit my language learning greatly as it is a large city. 1 (0.7%)
Because Tokyo is the capital city, therefore there would be more job opportunities for foreigners. 1 (0.7%)
Being such a big city, I think I'd be able to meet and interact with lots of different types of Korean people, and experience a lot of the history of Korea by visiting historical sites and exhibits. 1 (0.7%)
Big town means better opportunities 1 (0.7%)
(...)
13 prefuni_txt Preferred university while on SA character 0 (0.0%) 104 (73.8%)
Dokkyo 1 (0.7%)
Dokkyo University 1 (0.7%)
Either Rikkyo University or Kwansei Gakuin 1 (0.7%)
Hankuk University of Foreign Studies 1 (0.7%)
Hanyang University 2 (1.4%)
Hitotsubashi 1 (0.7%)
Hitotsubashi University. 1 (0.7%)
ICU UNIVERSITY 1 (0.7%)
Kanagawa University 1 (0.7%)
(...)
14 prefuni_reason_txt Why do you want to study there? character 0 (0.0%) 105 (74.5%)
As I have to fund the year myself the cheaper unis and accommodation are the focus for me 1 (0.7%)
Because I've done quite a bit of research into the University and it seems like it would be a good place to go to. It is not very far from central Tokyo, I have heard good things about it's programs, also before you enroll you are given a Japanese test to determine what classes you go into. I like this because it means I'm likely to be put into a class that I will find challenging enough to stay interested. 1 (0.7%)
Because I believe Waseda would push me to achieve the highest level of proficiency in Japanese. 1 (0.7%)
Because I think that the material that it offers would benefit my plans for the future compared to other universities in the area. 1 (0.7%)
Because of its historical past. 1 (0.7%)
Due to their business courses and good reputation with international students 1 (0.7%)
I feel that their choices and their teaching ways are suited for me. They focus a lot on grammar which I feel I need to improve the most on. 1 (0.7%)
I have been researching about this university and I have had native english speaking friends who have had their year abroad studying korean at this university and they said that they had the best time of their lives there. 1 (0.7%)
I have had good recommendations about them, and I have looked on the website and they look like they are great universities. 1 (0.7%)
(...)
15 expsa_other_txt If it's something else, please explain: character 0 (0.0%) 115 (81.6%)
- 1 (0.7%)
A good taste of life in japan 1 (0.7%)
Becoming more fluent in Japanese 1 (0.7%)
Being able to use the language in a day to day scenario and learning ways to improve without being in a class environment 1 (0.7%)
Being surrounded by the language and culture will help my learning of Japanese language 1 (0.7%)
Conversing with people in a language that is not my native one. 1 (0.7%)
Gaining a new level of respect for conflict in culture 1 (0.7%)
General confidence 1 (0.7%)
Getting started in the career I want 1 (0.7%)
(...)
16 cntlived_txt In which countries have you lived for longer than three months? character 0 (0.0%) 103 (73.0%)
Australia 1 (0.7%)
Barbados 1 (0.7%)
Brazil - However, this is via accumulation and not a fixed long term residency. i.e something up to a month at a time over several years. 1 (0.7%)
Bulgaria (my birth-country), and the UK 1 (0.7%)
Bulgaria, England 2 (1.4%)
Colombia and England 1 (0.7%)
England 1 (0.7%)
England and America 1 (0.7%)
England Algeria 1 (0.7%)
(...)
17 visited1_txt Country visited in childhood most memorable (1st mention) character 0 (0.0%) 30 (21.3%)
america 1 (0.7%)
America 7 (5.0%)
America (New york) 1 (0.7%)
Armenia 1 (0.7%)
Australia 3 (2.1%)
Barbados 1 (0.7%)
Belgium 2 (1.4%)
Brazil 1 (0.7%)
China 3 (2.1%)
(...)
18 visited2_txt Country visited in childhood most memorable (2nd mention) character 0 (0.0%) 46 (32.6%)
America 3 (2.1%)
Austria 3 (2.1%)
Belgium 1 (0.7%)
Bulgaria 2 (1.4%)
Burma 1 (0.7%)
Canada 2 (1.4%)
Croatia 2 (1.4%)
Cyprus 3 (2.1%)
Czechoslovakia 1 (0.7%)
(...)
19 visited3_txt Country visited in childhood most memorable (2nd mention) character 0 (0.0%) 67 (47.5%)
Abu Dhabi 1 (0.7%)
America 2 (1.4%)
America (New York) 2 (1.4%)
Amsterdam 1 (0.7%)
Barbados 1 (0.7%)
Belgium 1 (0.7%)
Croatia 1 (0.7%)
cyprus 1 (0.7%)
Denmark 1 (0.7%)
(...)
20 otherlang_txt What other language(s) do you speak? character 0 (0.0%) 84 (59.6%)
A bit of Scots English and French 1 (0.7%)
A little bit of French and Italian (not fluent) 1 (0.7%)
A little bit of Irish 1 (0.7%)
A little French and a little Spanish 1 (0.7%)
Arabic 1 (0.7%)
Beginners Norwegian 1 (0.7%)
Bulgarian 1 (0.7%)
Bulgarian, German, Russian, 1 (0.7%)
Chinese 1 (0.7%)
(...)
21 parotherlang_txt What language(s) do your parents/caregivers speak? character 0 (0.0%) 101 (71.6%)
Arabic and French 1 (0.7%)
Bulgarian 1 (0.7%)
Chinese 1 (0.7%)
Dutch, French, Spanish, German 1 (0.7%)
English and Dutch 1 (0.7%)
French 1 (0.7%)
French and a bit of Italian 1 (0.7%)
French and Italian 1 (0.7%)
French, German, English, learning Korean and Japanese, some Malagasy 1 (0.7%)
(...)
22 natlang_txt What is/are your native language(s)? character 0 (0.0%) Anguillian creole 1 (0.7%)
British English 1 (0.7%)
Bulgarian 1 (0.7%)
Bulgarian and English 1 (0.7%)
Catalan/Spanish 1 (0.7%)
Emglish 1 (0.7%)
english 2 (1.4%)
English 109 (77.3%)
English and Irish 1 (0.7%)
English and Welsh 2 (1.4%)
(...)
23 foccu_txt Father's / First caregiver's main occupation while at school character 0 (0.0%) 4 (2.8%)
- 2 (1.4%)
? 1 (0.7%)
Accountant 2 (1.4%)
Agriculture 1 (0.7%)
Alarm Engineer 1 (0.7%)
Audiologist 1 (0.7%)
Benefits officer 1 (0.7%)
Border Patrol 1 (0.7%)
Builder 2 (1.4%)
(...)
24 moccu_txt Mother's / Second caregiver's main occupation while at school character 0 (0.0%) 1 (0.7%)
Administrator 1 (0.7%)
Architect 1 (0.7%)
aromatherapist/reflexologist 1 (0.7%)
Assistant 1 (0.7%)
Assistant teacher 1 (0.7%)
Baker 1 (0.7%)
bartender/cleaner 1 (0.7%)
Business Manager 1 (0.7%)
Care Worker 1 (0.7%)
(...)
25 school_other_txt Other school type character 0 (0.0%) 126 (89.4%)
A Free school 1 (0.7%)
collage 1 (0.7%)
College 3 (2.1%)
Faith School 1 (0.7%)
Homeschooled till 14 and then college 1 (0.7%)
I did highschool in England and Australia 1 (0.7%)
Primary, Secondary and College 1 (0.7%)
Public school/sports college/performing arts school 1 (0.7%)
School in France 1 (0.7%)
(...)
26 sib1occ_study_txt What course was your (oldest) sibling studying? character 0 (0.0%) 121 (85.8%)
Art 1 (0.7%)
BA Philosophy and English Language 1 (0.7%)
Biomedical science 1 (0.7%)
Business (of some sort) 1 (0.7%)
Chinese & French 1 (0.7%)
creative music technology 1 (0.7%)
Criminology 1 (0.7%)
Film 1 (0.7%)
French and Spanish Language 1 (0.7%)
(...)
27 sib1occ_work_txt What was your (oldest) sibling line of work? character 0 (0.0%) 85 (60.3%)
Accountant 1 (0.7%)
Administration for husband's company 1 (0.7%)
An instructor at an outdoor activity centre 1 (0.7%)
Astrophysics 1 (0.7%)
Bar tender 1 (0.7%)
Bar Worker 1 (0.7%)
Bartender 1 (0.7%)
Beautician 1 (0.7%)
Beauty therapist 1 (0.7%)
(...)
28 sib2occ_study_txt What course was your second oldest sibling studying? character 0 (0.0%) 135 (95.7%)
Archeological and ancient history 1 (0.7%)
BA Philosophy 1 (0.7%)
Chemistry 1 (0.7%)
Criminology 1 (0.7%)
Jewellery and Metal Design BDes (Hons) 1 (0.7%)
Popular music and worship 1 (0.7%)
29 sib2occ_work_txt What was your second oldest sibling's line of work? character 0 (0.0%) 125 (88.7%)
Bar staff 1 (0.7%)
Beautician 1 (0.7%)
Caregiver 1 (0.7%)
Chef 1 (0.7%)
Data analyst 1 (0.7%)
Entertainment 1 (0.7%)
Fast food worker 1 (0.7%)
IT 1 (0.7%)
Jobseeker/Unemployed 1 (0.7%)
(...)
30 sib3occ_work_txt What was your third oldest sibling's line of work? character 0 (0.0%) 136 (96.5%)
Don’t know 1 (0.7%)
I don't know 1 (0.7%)
N/A 1 (0.7%)
Primary School teacher 1 (0.7%)
Steel worker 1 (0.7%)
31 sib4occ_work_txt What was your fourth oldest sibling's line of work? character 0 (0.0%) 138 (97.9%)
Builder 1 (0.7%)
N/A 1 (0.7%)
Unemployed 1 (0.7%)

Tabulations

Click to see code 
sa <- datawizard::data_read("data_in/sa2020.sav")

flextable::proc_freq(sa, "uni", "language")

uni

language

Japanese

Korean

Total

York St John University

Count

51 (36.2%)

54 (38.3%)

105 (74.5%)

Mar. pct (1)

64.6% ; 48.6%

87.1% ; 51.4%

The University of Sheffield

Count

8 (5.7%)

8 (5.7%)

Mar. pct

12.9% ; 100.0%

The University of Oxford

Count

2 (1.4%)

2 (1.4%)

Mar. pct

2.5% ; 100.0%

The University of Birmingham

Count

8 (5.7%)

8 (5.7%)

Mar. pct

10.1% ; 100.0%

Oxford Brookes University

Count

5 (3.5%)

5 (3.5%)

Mar. pct

6.3% ; 100.0%

Newcastle University

Count

6 (4.3%)

6 (4.3%)

Mar. pct

7.6% ; 100.0%

Cardiff University

Count

7 (5.0%)

7 (5.0%)

Mar. pct

8.9% ; 100.0%

Total

Count

79 (56.0%)

62 (44.0%)

141 (100.0%)

(1) Columns and rows percentages